Measuring Flexibility through Reduction Potential

TL;DR

This paper addresses the challenge of quantifying when and how much electric vehicle charging can be shifted to support grid operations. It introduces the reduction potential matrix, $M(\mathcal{X}, D, T) \in \mathbb{R}^{T \times D}$, with entries $m_{k,t}$ that quantify the load reduction potential over a $k$-hour window starting at time $t$, enabling explicit assessment of timing, magnitude, and duration of fleet flexibility under grid constraints. The approach sits between explicit and implicit characterizations, accommodating arbitrary constraints while preserving intuitive interpretation, and is demonstrated on simulated Virginia data for freight and transit fleets. Empirical results show substantial but group-dependent flexibility, peaking at different times (roughly 8 PM for freight and 1 AM for transit) and with transit fleets offering higher potential due to higher charging rates. The work provides a practical tool for rate design, demand response, and fleet operation planning, with future work on privacy, granularity, and extending to heavier-duty fleets.

Abstract

While electric vehicles (EVs) often exhibit substantial flexibility, harnessing this flexibility requires precise characterization of its timing and magnitude. This paper introduces the reduction potential matrix, a novel approach to EV load flexibility modeling which is both straightforward to calculate and intuitive to interpret. This paper demonstrates the approach by quantifying flexibility for two distinct commercial vehicle groups--freight vehicles and transit buses--using simulated charging data from Virginia. While both groups are found to have substantial flexibility, its properties vary across the groups. Naturally, this variability manifests in differences in each group's role as a grid resource. The paper concludes with a discussion on how system planners, fleet operators, and other stakeholders can use the matrix to assess and leverage EV flexibility.

Figures (4)

• Figure 1: Empirical dwell probability.
• Figure 2: Average and interquartile range of uncoordinated charging load.
• Figure 3: Slack time distribution.
• Figure 4: Average load reduction potential matrices.

Theorems & Definitions (3)

• Definition 1: Uncoordinated load
• Definition 2: Reduction potential
• Definition 3: Reduction potential matrix